TY - JOUR

T1 - GPS-aided video tracking

AU - Feuerhake, Udo

AU - Brenner, Claus

AU - Sester, Monika

PY - 2015/8/6

Y1 - 2015/8/6

N2 - Tracking moving objects is both challenging and important for a large variety of applications. Different technologies based on the global positioning system (GPS) and video or radio data are used to obtain the trajectories of the observed objects. However, in some use cases, they fail to provide sufficiently accurate, complete and correct data at the same time. In this work we present an approach for fusing GPS-and video-based tracking in order to exploit their individual advantages. In this way we aim to combine the reliability of GPS tracking with the high geometric accuracy of camera detection. For the fusion of the movement data provided by the different devices we use a hidden Markov model (HMM) formulation and the Viterbi algorithm to extract the most probable trajectories. In three experiments, we show that our approach is able to deal with challenging situations like occlusions or objects which are temporarily outside the monitored area. The results show the desired increase in terms of accuracy, completeness and correctness.

AB - Tracking moving objects is both challenging and important for a large variety of applications. Different technologies based on the global positioning system (GPS) and video or radio data are used to obtain the trajectories of the observed objects. However, in some use cases, they fail to provide sufficiently accurate, complete and correct data at the same time. In this work we present an approach for fusing GPS-and video-based tracking in order to exploit their individual advantages. In this way we aim to combine the reliability of GPS tracking with the high geometric accuracy of camera detection. For the fusion of the movement data provided by the different devices we use a hidden Markov model (HMM) formulation and the Viterbi algorithm to extract the most probable trajectories. In three experiments, we show that our approach is able to deal with challenging situations like occlusions or objects which are temporarily outside the monitored area. The results show the desired increase in terms of accuracy, completeness and correctness.

KW - Algorithm

KW - Object tracking

KW - Trajectory analysis, sensor and data fusion

UR - http://www.scopus.com/inward/record.url?scp=84948959319&partnerID=8YFLogxK

U2 - 10.3390/ijgi4031317

DO - 10.3390/ijgi4031317

M3 - Article

AN - SCOPUS:84948959319

VL - 4

SP - 1317

EP - 1335

JO - ISPRS International Journal of Geo-Information

JF - ISPRS International Journal of Geo-Information

SN - 2220-9964

IS - 3

ER -